Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.

A new algorithm solves complicated partial differential equations by breaking them down into simpler problems, potentially guiding computer graphics and geometry processing.


The three-day, hands-on conference hosted by the MIT RAISE Initiative welcomed youths and adults from nearly 30 countries.

AI agents could soon become indistinguishable from humans online. Could “personhood credentials” protect people against digital imposters?

The software tool NeuroTrALE is designed to quickly and efficiently process large amounts of brain imaging data semi-automatically.

In controlled experiments, MIT CSAIL researchers discover simulations of reality developing deep within LLMs, indicating an understanding of language beyond simple mimicry.

The approach can detect anomalies in data recorded over time, without the need for any training.

A new algorithm helps robots practice skills like sweeping and placing objects, potentially helping them improve at important tasks in houses, hospitals, and factories.

Leveraging more than 35 years of experience at MIT, Bertsimas will work with partners across the Institute to transform teaching and learning on and off campus.

CSAIL researchers introduce a novel approach allowing robots to be trained in simulations of scanned home environments, paving the way for customized household automation accessible to anyone.

More efficient than other approaches, the “Thermometer” technique could help someone know when they should trust a large language model.

Introducing structured randomization into decisions based on machine-learning model predictions can address inherent uncertainties while maintaining efficiency.

MAIA is a multimodal agent that can iteratively design experiments to better understand various components of AI systems.

Analysis and materials identified by MIT engineers could lead to more energy-efficient fuel cells, electrolyzers, batteries, or computing devices.

A new study shows someone’s beliefs about an LLM play a significant role in the model’s performance and are important for how it is deployed.

The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.

An MIT team uses computer models to measure atomic patterns in metals, essential for designing custom materials for use in aerospace, biomedicine, electronics, and more.

Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.

The approach could help engineers design more efficient energy-conversion systems and faster microelectronic devices, reducing waste heat.

A new technique enables users to compare several large models and choose the one that works best for their task.

Members of the MIT community, supporters, and guests commemorate the opening of the new college headquarters.

New CSAIL research highlights how LLMs excel in familiar scenarios but struggle in novel ones, questioning their true reasoning abilities versus reliance on memorization.

More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.

The challenge asked teams to develop AI algorithms to track and predict satellites’ patterns of life in orbit using passively collected data

Developed by MIT RAISE, the Day of AI curriculum empowers K-12 students to collaborate on local and global challenges using AI.

This new tool offers an easier way for people to analyze complex tabular data.

With decades of experience working across the laboratory’s R&D areas, Choi brings a focus on collaboration, technical excellence, and unity.

MosaicML, co-founded by an MIT alumnus and a professor, made deep-learning models faster and more efficient. Its acquisition by Databricks broadened that mission.

The award recognizes his contributions as director of MIT Lincoln Laboratory and as vice chair and chair of the Defense Science Board.

The program focused on AI in health care, drawing on Takeda’s R&D experience in drug development and MIT’s deep expertise in AI.

This technique could lead to safer autonomous vehicles, more efficient AR/VR headsets, or faster warehouse robots.

LLMs trained primarily on text can generate complex visual concepts through code with self-correction. Researchers used these illustrations to train an image-free computer vision system to recognize real photos.

The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.

Multimedia artist Jackson 2bears reimagines the Haudenosaunee longhouse and creation story.

Combining natural language and programming, the method enables LLMs to solve numerical, analytical, and language-based tasks transparently.

Co-hosted by the McGovern Institute, MIT Open Learning, and others, the symposium stressed emerging technologies in advancing understanding of mental health and neurological conditions.

The method uses language-based inputs instead of costly visual data to direct a robot through a multistep navigation task.

A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.

DenseAV, developed at MIT, learns to parse and understand the meaning of language just by watching videos of people talking, with potential applications in multimedia search, language learning, and robotics.

The technique characterizes a material’s electronic properties 85 times faster than conventional methods.

In the new economics course 14.163 (Algorithms and Behavioral Science), students investigate the deployment of machine-learning tools and their potential to understand people, reduce bias, and improve society.

The startup Augmental allows users to operate phones and other devices using their tongue, mouth, and head gestures.

With generative AI models, researchers combined robotics data from different sources to help robots learn better.

A new approach could streamline virtual training processes or aid clinicians in reviewing diagnostic videos.

Fifteen new faculty members join six of the school’s academic departments.

Graduate student Nolen Scruggs works with a local tenant association to address housing inequality as part of the MIT Initiative on Combatting Systemic Racism.

The 10 Design Fellows are MIT graduate students working at the intersection of design and multiple disciplines across the Institute.

A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.

A new algorithm learns to squish, bend, or stretch a robot’s entire body to accomplish diverse tasks like avoiding obstacles or retrieving items.

The conversation in Kresge Auditorium touched on the promise and perils of the rapidly evolving technology.